The delivery of a package from a consignor to a consignee typically requires sorting the package at several locations before the package reaches the final destination. A conventional delivery network typically includes a series of customer service centers that receive and deliver packages, and several intermediate hubs that provide links between the service centers. The flow of a package through this delivery network typically begins at a service center. From there, the package flows through a series of intermediate hubs before reaching the destination facility responsible for delivering the package to the destination address. Within each intermediate hub, the package is sorted according to the destination address for the package and consolidated for transport to the next intermediate hub or service center in the delivery process.
The tremendous volume of packages flowing through the intermediate hubs creates a logistical challenge. To date, sorting at the intermediate hubs is a highly manual process that relies heavily on the knowledge-base of the sorting operator. The sorting operator reads the destination address zip code and service level from a shipping label on a package and sorts the package to the appropriate conveyor belt, bin, or chute. The sorting location for each zip code is specified in a series of standard sorting charts. Sorting charts are well known in the industry and specify the next sorting facility the package will pass according to a delivery plan. These sorting charts are typically indexed according to destination zip code and the service level of the package, wherein the service level of a package represents the committed delivery time for the package. The efficiency of the sorting operation depends on how quickly the sorting operator determines the appropriate sorting location for a package. To improve the efficiency, sorting operators memorize the zip codes associated with each sorting location and use the sorting charts sparingly. This highly manual process often results in sorting errors.
Typically, a sortation facility is directly linked to only a few sortation hubs in the network as shown in FIG. 1. However, packages may be sorted based on facilities further downstream in the delivery process. For example, assume the delivery plan for a package specifies that the package will pass through Hubs A, B and C in sequence. The sorting process at Hub A may include consolidating packages bound for Hub C into a container even though Hub A is not directly connected to Hub C. When this container arrives at Hub B, the operator only has to sort the single large container rather than several smaller packages because the packages were presorted at Hub A. This process reduces the overall handling of the packages. But, this consolidation practice is limited by the ability of sort operators to remember which packages are sorted to which location. A need therefore exists for processes to identify the sort locations that do no rely on the memory of the sorting operators. Because traditional sort processes rely so heavily on the knowledge-base of the sort operators, there is a natural hesitancy to change a sort plan that results in a change to the knowledge-base. The learning curve necessary to implement a change creates significant inefficiencies and increases the opportunity for sorting mistakes. Accordingly, any change to a sort plan must be weighed against the confusion caused by the change. As a result, many timesaving adjustments to sorting charts are discarded.
Therefore an unsatisfied need exists for improved systems and methods for sorting packages within a delivery network that overcome the deficiencies in the prior art, some of which are discussed above.